Optimizing Resource Allocation for 6G NOMA-enabled Cooperative Vehicular Networks

This paper proposes a new optimization framework for NOMA-enabled cooperative vehicular network. In particular, we jointly optimize the vehicle paring, channel assignment, and power allocation at source and relaying vehicles. The objective is to maximize the sum rate of the system subject to the power allocation, minimum rate, relay battery lifetime and successive interference cancellation constraints. To solve the joint optimization problem efficiently, we adopt dual theory followed by Karush-Kuhn-Tucker (KKT) conditions, where the dual variables are iteratively computed through sub-gradient method. Two less complex suboptimal optimization schemes are also presented as the benchmark cooperative vehicular schemes.